A wide variety of biological processes and signals are mediated by patterns detectable at the sequence level in proteins, DNA and RNA. For example, one facet of transcriptional regulation of genes involves proteins (transcription factors) recognizing and binding to specific DNA sequence patterns. Other examples of important biological sequence patterns include protein structural domains, microRNAsand the protein target sequences of kinases. The MEME suite of bioinformatics software tools provide biologists with powerful methods for discovering, analyzing and interpreting biological sequence patterns of many types, including those mentioned above. The suite includes onetool - MEME -- that biologists useto discover novel sequence patterns (motifs), and three tools -- Meta-MEME, MCAST and MAST -- that biologists use to search sequence databases for matches to motif-based sequence models. This grant will enable us to dramatically improve the scientific value of the suite to the thousands of biologists who already use it. These improvements will be visible to the biologist using the suite as increased availability, better support, better user-interface and documentation, more powerful algorithms, better interoperability, and faster release cycles. We will achieve these goals via a combination of three specific aims: (1) improved software engineering, (2) ongoing support and (3) continued software development of the suite.